Journal of Public Health

, Volume 21, Issue 1, pp 87–95 | Cite as

A low response rate does not necessarily indicate non-response bias in gastroenterology survey research: a population-based study

  • Rok Seon Choung
  • G. Richard LockeIII
  • Cathy D. Schleck
  • Jeanette Y. Ziegenfuss
  • Timothy J. Beebe
  • Alan R. Zinsmeister
  • Nicholas J. Talley
Original Article



To estimate the potential for response bias in standard mailed questionnaires used in surveys of GI symptoms in a community.

Subjects and methods

Validated self-report tools have been developed to measure functional gastrointestinal (GI) disorders but response rates in community surveys have been rapidly declining in many parts of the world. Whether a lower community response rate introduces significant response bias in GI survey research is unknown. A questionnaire was mailed to a total of 5,069 randomly selected subjects. The overall response rate was 52 %. A random sample of 723 of these subjects (428 responders and 295 non-responders, stratified by age and gender) was selected for medical record abstraction (including both inpatient and outpatient history).


The odds for response increased in those with a higher body mass index (odds ratio (OR):1.02 [95 % CI: 1.01, 1.03]), more health care seeking behavior for non-GI problems (OR: 1.97 [95 % CI: 1.43, 2.72]), and for those who had responded to a previous survey (OR: 4.84 [95 % CI: 2.84, 8.26]). Responder status was not significantly associated with any GI symptoms or a diagnosis of GI or non-GI disease (with two exceptions, diverticulosis and skin disease).


Despite a response rate of only 52 %, the results of a community-based GI survey do not appear to be impacted by non-response bias in a major way. A low survey response rate does not necessarily indicate non-response bias.


Response Bias Gastrointestinal surveys Population 



The authors wish to thank Johannes von Blumenthal, who was a medical student of Paracelsus Medizinische Privatuniversitat, Austria, for his assistance with the chart reviews.

Financial Support

This study was made possible in part by the Rochester Epidemiology Project (Grant no. R01-AR30582 from the National Institute of Arthritis and Musculoskeletal and Skin Diseases).

Conflict of Interest

The authors declare they have no conflict of interest.


  1. Atrostic BK, Bates N, Burt G, Silberstein A (2001) Nonresponse in US Government household surveys: consistent measures, recent trends, and new insights. J Off Stat 17(2):209–226Google Scholar
  2. Bakke P, Gulsvik A, Lilleng P, Overa O, Hanoa R, Eide GE (1990) Postal survey on airborne occupational exposure and respiratory disorders in Norway: causes and consequences of non-response. J Epidemiol Community Health 44(4):316–320PubMedCrossRefGoogle Scholar
  3. Barton J, Bain C, Hennekens CH, Rosner B, Belanger C, Roth A et al (1980) Characteristics of respondents and non-respondents to a mailed questionnaire. Am J Public Health 70(8):823–825PubMedCrossRefGoogle Scholar
  4. Beard CM, Lane AW, O'Fallon WM, Riggs BL, Melton LJ 3rd (1994) Comparison of respondents and nonrespondents in an osteoporosis study. Ann Epidemiol 4(5):398–403PubMedCrossRefGoogle Scholar
  5. Beebe TJ, Talley NJ, Camilleri M, Jenkins SM, Anderson KJ, Locke GR 3rd (2007) The HIPAA authorization form and effects on survey response rates, nonresponse bias, and data quality: a randomized community study. Med Care 45(10):959–965PubMedCrossRefGoogle Scholar
  6. Brehm JO (1993) The phantom respondents: opinion surveys and political representation. University of Michigan Press, Ann Arbor, MIGoogle Scholar
  7. Castillo EJ, Camilleri M, Locke GR, Burton DD, Stephens DA, Geno DM et al (2004) A community-based, controlled study of the epidemiology and pathophysiology of dyspepsia. Clin Gastroenterol Hepatol 2(11):985–996PubMedCrossRefGoogle Scholar
  8. Chou P, Kuo HS, Chen CH, Lin HC (1997) Characteristics of non-participants and reasons for non-participation in a population survey in Kin-Hu, Kinmen. Eur J Epidemiol 13(2):195–200PubMedCrossRefGoogle Scholar
  9. Choung RS, Locke GR, Schleck CD, Zinsmeister AR, Talley NJ (2007a) Do distinct dyspepsia subgroups exist in the community? A population-based study. Am J Gastroenterol 102(9):1983–1989PubMedCrossRefGoogle Scholar
  10. Choung RS, Locke GR 3rd, Zinsmeister AR, Schleck CD, Talley NJ (2007b) Epidemiology of slow and fast colonic transit using a scale of stool form in a community. Aliment Pharmacol Ther 26(7):1043–1050PubMedCrossRefGoogle Scholar
  11. Criqui MH, Barrett-Connor E, Austin M (1978) Differences between respondents and non-respondents in a population-based cardiovascular disease study. Am J Epidemiol 108(5):367–372PubMedGoogle Scholar
  12. Dallosso HM, Matthews RJ, McGrother CW, Clarke M, Perry SI, Shaw C et al (2003) An investigation into nonresponse bias in a postal survey on urinary symptoms. BJU Int 91(7):631–636PubMedCrossRefGoogle Scholar
  13. de Leeuw E, de Heer W (2002) Trends in household survey nonresponse: a longitudinal and international comparison. In: Groves RM, Dillman DA, Eltinge JL, Little RJA (eds) survey nonresponse. Wiley, New York, pp 41–54Google Scholar
  14. Dunn JP, Hawkes R (1966) Comparison of respondents and nonrespondents in a periodic health examination program to a mailed questionnaire. Am J Public Health Nations Health 56(2):230–236PubMedCrossRefGoogle Scholar
  15. Eagan TM, Eide GE, Gulsvik A, Bakke PS (2002) Nonresponse in a community cohort study: predictors and consequences for exposure-disease associations. J Clin Epidemiol 55(8):775–781PubMedCrossRefGoogle Scholar
  16. Elliott MN, Edwards C, Angeles J, Hambarsoomians K, Hays RD (2005) Patterns of unit and item nonresponse in the CAHPS® Hospital Survey. Health Serv Res 40(6 pt 2):2096–2119PubMedCrossRefGoogle Scholar
  17. Goldberg M, Chastang JF, Leclerc A, Zins M, Bonenfant S, Bugel I et al (2001) Socioeconomic, demographic, occupational, and health factors associated with participation in a long-term epidemiologic survey: a prospective study of the French GAZEL cohort and its target population. Am J Epidemiol 154(4):373–384PubMedCrossRefGoogle Scholar
  18. Groves RM (1989) Survey errors and survey costs. Wiley, New YorkCrossRefGoogle Scholar
  19. Groves RM (2006) Nonresponse rates and nonresponse bias in household surveys. Public Opin Q 70(5):646–675CrossRefGoogle Scholar
  20. Groves RM, Peytcheva E (2008) The impact of nonresponse rates on nonresponse bias: a meta-analysis. Public Opin Q 72(2):167–189CrossRefGoogle Scholar
  21. Hara M, Sasaki S, Sobue T, Yamamoto S, Tsugane S (2002) Comparison of cause-specific mortality between respondents and nonrespondents in a population-based prospective study: ten-year follow-up of JPHC Study Cohort I. Japan Public Health Center. J Clin Epidemiol 55(2):150–156PubMedCrossRefGoogle Scholar
  22. Harald K, Salomaa V, Jousilahti P, Koskinen S, Vartiainen E (2007) Non-participation and mortality in different socioeconomic groups: the FINRISK population surveys in 1972–92. J Epidemiol Community Health 61(5):449–454PubMedCrossRefGoogle Scholar
  23. Hardie JA, Bakke PS, Morkve O (2003) Non-response bias in a postal questionnaire survey on respiratory health in the old and very old. Scand J Public Health 31(6):411–417PubMedCrossRefGoogle Scholar
  24. Hartge P (1999) Raising response rates: getting to yes. Epidemiology 10(2):105–107PubMedCrossRefGoogle Scholar
  25. Heilbrun LK, Ross PD, Wasnich RD, Yano K, Vogel JM (1991) Characteristics of respondents and nonrespondents in a prospective study of osteoporosis. J Clin Epidemiol 44(3):233–239PubMedCrossRefGoogle Scholar
  26. Hoeymans N, Feskens EJ, Van Den Bos GA, Kromhout D (1998) Non-response bias in a study of cardiovascular diseases, functional status and self-rated health among elderly men. Age Ageing 27(1):35–40PubMedCrossRefGoogle Scholar
  27. Holle R, Hochadel M, Reitmeir P, Meisinger C, Wichmann HE (2006) Prolonged recruitment efforts in health surveys: effects on response, costs, and potential bias. Epidemiology 17(6):639–643PubMedCrossRefGoogle Scholar
  28. Hox JJ, de Leeuw ED (1994) A comparison of nonresponse in mail, telephone, and face-to-face surveys. Qual Quant 28(4):329–344CrossRefGoogle Scholar
  29. Jacobsen SJ, Xia Z, Campion ME, Darby CH, Plevak MF, Seltman KD et al (1999) Potential effect of authorization bias on medical record research. Mayo Clin Proc 74(4):330–338PubMedCrossRefGoogle Scholar
  30. Jooste PL, Yach D, Steenkamp HJ, Botha JL, Rossouw JE (1990) Drop-out and newcomer bias in a community cardiovascular follow-up study. Int J Epidemiol 19(2):284–289PubMedCrossRefGoogle Scholar
  31. Keeter S, Miller C, Kohut A, Groves RM, Presser S (2000) Consequences of reducing nonresponse in a national telephone survey. Public Opin Q 64(2):125–148PubMedCrossRefGoogle Scholar
  32. Kim J, Lonner JH, Nelson CL, Lotke PA (2004) Response bias: effect on outcomes evaluation by mail surveys after total knee arthroplasty. J Bone Joint Surg Am 86-A(1):15–21PubMedGoogle Scholar
  33. Korkeila K, Suominen S, Ahvenainen J, Ojanlatva A, Rautava P, Helenius H et al (2001) Non-response and related factors in a nation-wide health survey. Eur J Epidemiol 17(11):991–999PubMedCrossRefGoogle Scholar
  34. Launer LJ, Wind AW, Deeg DJ (1994) Nonresponse pattern and bias in a community-based cross-sectional study of cognitive functioning among the elderly. Am J Epidemiol 139(8):803–812PubMedGoogle Scholar
  35. Macera CA, Jackson KL, Davis DR, Kronenfeld JJ, Blair SN (1990) Patterns of non-response to a mail survey. J Clin Epidemiol 43(12):1427–1430PubMedCrossRefGoogle Scholar
  36. Melton LJ 3rd (1996) History of the Rochester Epidemiology Project. Mayo Clin Proc 71(3):266–274PubMedCrossRefGoogle Scholar
  37. Melton LJ 3rd (1997) The threat to medical-records research. N Engl J Med 337(20):1466–1470PubMedCrossRefGoogle Scholar
  38. Melton LJ 3rd, Dyck PJ, Karnes JL, O'Brien PC, Service FJ (1993) Non-response bias in studies of diabetic complications: the Rochester Diabetic Neuropathy Study. J Clin Epidemiol 46(4):341–348PubMedCrossRefGoogle Scholar
  39. Milne JS, Maule MM, Williamson J (1971) Method of sampling in a study of older people with a comparison of respondents and non-respondents. Br J Prev Soc Med 25(1):37–41PubMedGoogle Scholar
  40. Morton LM, Cahill J, Hartge P (2006) Reporting participation in epidemiologic studies: a survey of practice. Am J Epidemiol 163(3):197–203PubMedCrossRefGoogle Scholar
  41. Nohr EA, Frydenberg M, Henriksen TB, Olsen J (2006) Does low participation in cohort studies induce bias? Epidemiology 17(4):413–418PubMedCrossRefGoogle Scholar
  42. Oremus M, Wolfson C (2004) Female specialists were more likely to respond to a postal questionnaire about drug treatments for Alzheimer disease. J Clin Epidemiol 57(6):620–623PubMedCrossRefGoogle Scholar
  43. Paganini-Hill A, Hsu G, Chao A, Ross RK (1993) Comparison of early and late respondents to a postal health survey questionnaire. Epidemiology 4(4):375–379PubMedCrossRefGoogle Scholar
  44. Richiardi L, Boffetta P, Merletti F (2002) Analysis of nonresponse bias in a population-based case:control study on lung cancer. J Clin Epidemiol 55(10):1033–1040PubMedCrossRefGoogle Scholar
  45. Sackett DL (1979) Bias in analytic research. J Chronic Dis 32(1–2):51–63PubMedCrossRefGoogle Scholar
  46. Shahar E, Folsom AR, Jackson R (1996) The effect of nonresponse on prevalence estimates for a referent population: insights from a population-based cohort study. Atherosclerosis Risk in Communities (ARIC) Study Investigators. Ann Epidemiol 6(6):498–506PubMedCrossRefGoogle Scholar
  47. Shen M, Cozen W, Huang L, Colt J, De Roos AJ, Severson RK et al (2008) Census and geographic differences between respondents and nonrespondents in a case-control study of non-Hodgkin lymphoma. Am J Epidemiol 167(3):350–361PubMedCrossRefGoogle Scholar
  48. Sonne-Holm S, Sorensen TI, Jensen G, Schnohr P (1989) Influence of fatness, intelligence, education and sociodemographic factors on response rate in a health survey. J Epidemiol Community Health 43(4):369–374PubMedCrossRefGoogle Scholar
  49. Steeh C, Kirgis N, Cannon B, DeWitt J (2001) Are they really as bad as they seem? Nonresponse rates at the end of the twentieth century. J Off Stat 17(2):227–247Google Scholar
  50. Talley NJ, Phillips SF, Melton J 3rd, Wiltgen C, Zinsmeister AR (1989) A patient questionnaire to identify bowel disease. Ann Intern Med 111(8):671–674PubMedGoogle Scholar
  51. Talley NJ, Zinsmeister AR, Van Dyke C, Melton LJ 3rd (1991) Epidemiology of colonic symptoms and the irritable bowel syndrome. Gastroenterology 101(4):927–934PubMedGoogle Scholar
  52. Talley NJ, Weaver AL, Zinsmeister AR, Melton LJ 3rd (1992) Onset and disappearance of gastrointestinal symptoms and functional gastrointestinal disorders. Am J Epidemiol 136(2):165–177PubMedGoogle Scholar
  53. Tickle M, Milsom KM, Blinkhorn AS, Worthington HV (2003) Comparing different methods to detect and correct nonresponse bias in postal questionnaire studies. J Public Health Dent 63(2):112–128PubMedCrossRefGoogle Scholar
  54. Van Loon AJ, Tijhuis M, Picavet HS, Surtees PG, Ormel J (2003) Survey non-response in the Netherlands: effects on prevalence estimates and associations. Ann Epidemiol 13(2):105–110PubMedCrossRefGoogle Scholar
  55. West R, McEwen A, Bolling K, Owen L (2001) Smoking cessation and smoking patterns in the general population: a 1-year follow-up. Addiction 96(6):891–902PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Rok Seon Choung
    • 1
    • 5
  • G. Richard LockeIII
    • 1
  • Cathy D. Schleck
    • 2
  • Jeanette Y. Ziegenfuss
    • 3
  • Timothy J. Beebe
    • 3
  • Alan R. Zinsmeister
    • 2
  • Nicholas J. Talley
    • 4
  1. 1.Enteric Neuroscience Program, Division of Gastroenterology and HepatologyMayo ClinicRochesterUSA
  2. 2.Division of Biomedical Statistics and InformaticsMayo ClinicRochesterUSA
  3. 3.Division of Health Care Policy and ResearchMayo ClinicRochesterUSA
  4. 4.Faculty of HealthUniversity of NewcastleCallaghanAustralia
  5. 5.Division of Gastroenterology and HepatologyCollege of Medicine, Korea UniversitySeoulKorea

Personalised recommendations